The basic idea is simplicity itself. A belief in a single intelligence assumes that we have one central, all-purpose computer—and it determines how well we perform in every sector of life. In contrast, a belief in multiple intelligences assumes that we have a number of relatively autonomous computers—one that computes linguistic information, another spatial information, another musical information, another information about other people, and so on.

Gardner goes on to explain why MI does not in fact mean the same thing as “learning styles”, and points out that there is no evidence of the benefit of trying to teach to multiple learning styles.

Following that came a link to an actually older article by Daniel Willingham which discusses the problems with Gardner’s MI theory itself. The biggest takeaway from the article (which matches what I learned studying intro Ed Psych a few years ago) is that the data on intelligences supports multiple, hierarchical intelligences. There is evidence for separate mathematical and verbal intelligence, plus a controlling general intelligence “g” factor that influences them both.

It is important to bear in mind that the hierarchical model described in the previous section is not a theory, but a pattern of data. It is a description of how test scores are correlated. A theory of intelligence must be consistent with these data; the pattern of data is not itself a theory. For example, the data do not tell us what g is or how it works. The data tell us only that there is some factor that contributes to many intellectual tasks, and if your theory does not include such a factor, it is inconsistent with existing data. Gardner’s theory has that problem.

In other words, Gardner’s theory not only seems flawed, but Gardner is completely misrepresenting the discussion by only comparing his theory to a “one unified intelligence factor” theory. He’s still trying to make his theory sound good by comparing it to a model that psychologists have rejected for something like half a century.

Okay, great. So with that summed up, here’s what I’d really like to explore: why do people fall in love with both MI and “learning styles” in the first place?

I know of fantastic, clever and thoughtful teachers who dislike having these theories shot down because they’ve seen something good in applying them. I think we need to call out that good, maybe find a way to reframe it and hold it up as being valuable and defensible without needing MI or learning styles language.

Both Gardner and Willingham take a stab in this direction. Gardner gives the following advice that highlights the appeal of a “learning styles” mentality:

1. Individualize your teaching as much as possible. Instead of “one size fits all,” learn as much as you can about each student, and teach each person in ways that they find comfortable and learn effectively. …

2. Pluralize your teaching. Teach important materials in several ways, not just one (e.g. through stories, works of art, diagrams, role play). In this way you can reach students who learn in different ways. Also, by presenting materials in various ways, you convey what it means to understand something well. If you can only teach in one way, your own understanding is likely to be thin.

To me this hits exactly what people want to hear when they’re taught about multiple learningstyleintellwhatevers. And the reason is it’s great advice. But it’s great for reasons that probably have nothing to do with intelligence models. Is getting to know your students and connecting learning with their interests a good idea? Heck yes of course! Students learn more from a teacher who actually cares about them. Students need mentors who invest in their lives.

Is presenting new material in multiple ways a good idea? Heck yes of course! Off the top of my head I am pretty sure this is evidence-based and everything. If we really want to connect this to cognitive science somehow, we could point out that connecting new material to existing things-that-the-students-know helps them remember it, is how the brain wires thoughts together, and the more connections you make the more likely they will recall it. (But notice that you could just cut the “brain wiring” bit out of that last sentence and it’d be just as clear and could still be verified.)

Willingham points out another reason that MI hits the “like this” trigger in our minds:

Great intelligence researchers–Cyril Burt, Raymond Cattell, Louis Thurstone–discussed many human abilities, including aesthetic, athletic, musical, and so on. The difference was that they called them talents or abilities, whereas Gardner has renamed them intelligences. Gardner has pointed out on several occasions that the success of his book turned, in part, on this new label: “I am quite confident that if I had written a book called ‘Seven Talents’ it would not have received the attention thatFrames of Mind received.” Educators who embraced the theory might well have been indifferent to a theory outlining different talents–who didn’t know that some kids are good musicians, some are good athletes, and they may not be the same kids?

When contrasting MI with a “unified intelligence” model, it’s not difficult to see why teachers would grab onto MI. To say that all students contain a single variable that ranges from “smart” to “er, not smart” stings when you think of the wild variety of skills and talents that students have. Kids who shine in one area may look incompetent in another – but they DO shine somewhere, and a psychology that seems to ignore that sounds heartless.

There are two things to extract here. One is that those teachers were right about intelligence – the data supports them. The problem was that Gardner’s MI went too far, creating vague “intelligences” that seem only to amount to prior knowledge and experience and strongly stating their independence even when the data does not support it. The layered, hierarchical model that the data supports does show that some kids may be incredibly well-spoken and insightful but still struggle with mathematical reasoning.

The other question here is how much any of this has to do with overall “intelligence”, or whether it all boils down to past experience, domain-specific knowledge and self-efficacy. Within any one of these intelligence models, it’s possible for someone to have significantly more botanical knowledge than the average. Does this mean they have a uniquely high “intelligence” in that area, or does it just mean they’ve learned a lot of knowledge in the domain of botany? I want to believe (although don’t know for certain) that psychologists working in the area of psychometrics try to take this into account as they test their models. But for the teacher looking only at the bare structure of the theory, it may be easy to forget that neither model excludes the possibility of students who excel through past experience.

So.

Let’s keep telling people to use multiple representations – preferably meaningful ones – to teach their subject. Let’s keep telling teachers to get to know their students and individualize things where they can. Let’s also stop promoting poor models of the mind. We don’t need to hold onto flawed theories to be able to keep the good stuff that came from applying them.